Content extractor

ABSTRACT

Systems and methods for extracting data related to product sales and businesses that sell products are disclosed. The method may include obtaining a database connection parameter and a remote system connection parameter. The method also may include establishing a connection with a database using the database connection parameter, where the database has a table with a table attribute. Additionally, the method may include obtaining a mapping of one of the table attributes to a predefined attribute so that data may be extracted from the database using the mapping. The method may further include establishing a connection with a remote system using the remote system connection parameter and transmitting the extracted data to the remote system.

CROSS REFERENCE TO RELATED APPLICATION

This patent application claims priority under 35 U.S.C. §119 to U.S. Patent Application No. 61/364,780, entitled, “Point of Sale Data Collection,” filed Jul. 15, 2010, the complete disclosure of which is hereby fully incorporated herein by reference.

TECHNICAL FIELD

The present disclosure relates generally to collecting data related to product sales and businesses that sell products. According to exemplary embodiments, point of sale (POS) data is intercepted as it is sent from a POS scanner to a POS application running on a POS terminal. In the same or additional embodiments, software interfaces with, and extracts data from (e.g., POS data, inventory data, store data, etc.), an existing database containing information related to product sales and businesses that sell products. This data may be located on a datastore located in-store, in a corporate back office, or any other location.

BACKGROUND

Computer networks, such as the internet, enable transmission and reception of a vast array of information. In recent years, for example, some commercial retail stores have attempted to make product inventory information and other data related to product sales available to customers over the internet. However, most of this information is stored in legacy systems, from which it is time consuming and expensive to obtain. As a result, much of the online information provided by individual retailers is inaccurate. Similarly, a number of third party businesses have attempted to organize local product information (e.g., by scraping websites or other systems that expose product information, etc.) across multiple retailers and to provide the information over the internet. These attempts have also not been successful, likely due to difficulties accessing reliable data with high coverage of products, retailers, and locations.

Thus, a need exists in the art for a system that provides customers with accurate local product information covering multiple products, retailers, and locations.

SUMMARY

In accordance with one aspect of the invention, a method for extracting data related to product sales and businesses that sell products is disclosed. The method may include receiving a database connection parameter and a remote system connection parameter. The method also may include establishing a connection with a database using the database connection parameter, where the database has a table with a table attribute. Additionally, the method may include receiving a mapping of one of the table attributes to a predefined attribute, and extracting data from the database based the mapping. The method may further include establishing a connection with a remote system using the remote system connection parameter and transmitting the extracted data to the remote system.

In accordance with another aspect of the invention, a data extraction system is disclosed. The system may include a storage resource, a network module, a database including a table with one or more table attributes, and a processor communicatively coupled to the storage resource and the network module. The processor may execute application code instruction that may be stored in the storage resource. The instructions may cause the data extraction system to receive a database connection parameter, a remote system connection parameter, and a mapping of at least one table attribute to a predefined attribute. In addition, the instructions may cause the data extraction system to establish a connection with the database using the database connection parameter. Further, the instructions may further cause the data extraction system to extract data from the database based on the mapping, to process the extracted data, and to establish (via the network module) a connection with a remote system using the remote connection parameter. Finally, the instructions may cause the data extraction system to transmit (via the network module) the processed data to the remote system.

According to another aspect of the invention, a data extraction system is disclosed. The system may include one or more processors for executing programs, a network interface for receiving and transmitting data, a storage resource containing one or more data objects, and a data extraction engine that is executable by the one or more processors. Each data object may have one or more attributes. In addition, the data extraction engine may include instructions for obtaining a mapping of the one or more attributes to one or more predefined attributes, instructions for extracting data from the storage resource based on the mapping, and instructions for transmitting the data to a remote system via the network interface.

According to a further aspect of the invention, a computer program product is disclosed. The computer program product may be for use in conjunction with a computer system and a database including a table having one or more table attributes. The computer program product may include a computer readable storage medium and a computer program mechanism embedded therein. Additionally, the computer program mechanism may include instructions for receiving a database connection parameter, a remote system connection parameter, and a mapping of at least one table attribute to a predefined attribute. The computer program mechanism may further include instructions for establishing a connection with the database using the database connection parameter, instructions for extracting data from the database based on the mapping, and instructions for establishing a connection with a remote system using the remote system connection parameter. Finally, the computer program mechanism may include instructions for transmitting the processed data to the remote system.

According to still another aspect of the invention, a computer program product is disclosed. The computer program product may be for use in conjunction with a computer system and a database including data objects having one or more attributes. The computer program product may include a computer readable storage medium and a computer program mechanism embedded therein. Additionally, the computer program mechanism may include instructions for receiving a mapping of at least one data object attribute to a predefined attribute, instructions for extracting data from the database based on the mapping, and instructions for transmitting the extracted data to a remote system.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a system for collecting POS data, in accordance with certain exemplary embodiments.

FIG. 2 depicts a system for collecting POS data, in accordance with certain exemplary embodiments.

FIG. 3 depicts a block diagram of POS data collector, in accordance with certain exemplary embodiments.

FIG. 4 is a block flow diagram depicting a method for collecting POS data, in accordance with certain exemplary embodiments.

FIG. 5 depicts a system for extracting data, in accordance with certain exemplary embodiments.

FIG. 6 depicts a system for extracting data, in accordance with certain exemplary embodiments.

FIG. 7 depicts a system for extracting data, in accordance with certain exemplary embodiments.

FIG. 8 is a block flow diagram depicting a method for extracting data, in accordance with certain exemplary embodiments.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

The methods and systems described herein enable collection of the world's local point of sale (POS) data and other information related to product sales and businesses that sell products.

According to certain exemplary embodiments, a POS data collection system can include a POS data collector that is implemented as a hardware device and/or in software. The adapter may be installed at the point of sale in retail stores, for example, between a barcode scanner and the POS application running on a POS terminal (e.g., the cash register). When a product is scanned at the point of sale, the adapter may intercept the barcode as it is transmitted from the barcode scanner to the POS application. After intercepting the barcode, the adapter may transmit the barcode to the POS application without noticeable delay, so that the adapter does not interrupt standard business processes. In addition, the adapter may send the barcode to a remote server via a network connection. In this manner, the remote server may collect POS data that covers a significant number of products, retailers, and locations.

In the same or additional embodiments, a data collection system can include a content extractor that is implemented in software. The content extractor may be installed on a commercial retailer's local computer system, and may be used to extract information related to product sales and/or the commercial retailer itself. For example, many commercial retailers have local computer systems that store product inventory information, point of sale data, store listings (e.g., businesses with more than one location), product listings (e.g., all products for sale), price-quantity data (e.g., per store, per product pricing), store maps, circulars, coupons, etc. This and other data related to product sales and the business that sells products may be stored in a commercial retailer's local computer system.

This data may be stored in a commercially available database format (e.g., MySQL, Oracle, MS SQL Server, etc.) or according to other known methods (e.g., product inventory/sales software, flat file, spreadsheet, etc.). According to certain exemplary embodiments, the content extractor may be used to easily and intuitively interface to the information stored in such a database (or other known format) so that the data may be extracted and sent to a remote computer via a network connection. For example, the content extractor may provide a user interface to easily and intuitively map existing database attributes to those expected by the remote computer, and to easily and intuitively schedule a one-time, periodic, and/or real-time transmission of the extracted data to the remote computer. In this manner, the remote computer may collect information that covers a significant number of products, retailers, and locations.

One or more aspects of the invention may comprise a computer program that embodies the functions described and illustrated herein. However, it should be apparent that there could be many different ways of implementing the invention in computer programming, and the invention should not be construed as limited to any one set of computer program instructions. Further, a skilled programmer would be able to write such a computer program to implement an embodiment of the disclosed invention based on the appended flow charts and associated description in the application text. Therefore, disclosure of a particular set of program code instructions is not considered necessary for an adequate understanding of how to make and use the invention. The inventive functionality of the invention will be explained in more detail in the following description, read in conjunction with the figures illustrating the program flow.

Turning now to the drawings, in which like numerals indicate like elements throughout the figures, exemplary embodiments of the invention are described in detail.

FIG. 1 depicts a system 100 for collecting POS data, in accordance with certain exemplary embodiments. As depicted in FIG. 1, system 100 may comprise POS data collector 105, POS scanner 110, POS terminal 115, and remote system 150. POS data collector 105 may be connected to POS scanner 110 via connection 120, and to POS terminal 115 via connection 125. POS data collector 105 may communicate with POS scanner 110 and POS terminal 115 using any standard or proprietary storage and/or communication protocol, including without limitation, universal serial bus (USB), RS-232, and/or any combination thereof. And while the embodiment in FIG. 1 depicts wired connections 120 and 125, either or both of these connections may be replaced with a wireless communication link (e.g., Wi-Fi, MiFi, Bluetooth, etc.) in accordance with certain other exemplary embodiments. Additionally, while POS data collector 105 is depicted as a standalone hardware device in FIGS. 1 and 2, one or more components of POS data collector 105 may be integrated into one or both of POS scanner 110 and POS terminal 115, in accordance with alternative exemplary embodiments.

As depicted in FIG. 1, the POS scanner 110 may be a traditional wired, generally stationary barcode scanner, in accordance with certain exemplary embodiments. FIG. 2 depicts system 200 according to an alternative embodiment wherein POS scanner includes POS wireless barcode scanner 212 and POS wireless base station 210. In this alternative embodiment, POS data collector 105 may communicate with POS wireless base station 210 in the same way the POS data collector 105 communicates with POS scanner 110 of FIG. 1. While FIGS. 1 and 2 illustrate different exemplary embodiments, it should be appreciated that the POS data collector 105 may be used similarly in POS systems with hardware that varies from that depicted in FIGS. 1 and 2.

According to an exemplary embodiment, POS scanner 110 may be a barcode scanner and may be configured to read any number of barcode formats, including without limitation UPC, EAN, JAN, etc. According to other exemplary embodiments, POS scanner 110 may be an RFID reader or any other device that is capable of reading product identifier information in a POS system.

As further depicted in FIG. 1, POS data collector 105 may be communicatively coupled to remote system 150 via network 140. Network 140 may be implemented as, or may be a part of, a storage area network (SAN), personal area network (PAN), local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a wireless local area network (WLAN), a virtual private network (VPN), an intranet, the Internet or any other appropriate architecture or system that facilitates the communication of signals, data and/or messages (generally referred to as data). POS data collector 105 may connect to network 140 via connection 135. According to an exemplary embodiment, connection 135 may be a dedicated cellular modem connection. In an alternative embodiment, connection 135 may be a wired Ethernet connection, a Wi-Fi or Bluetooth connection to a hotspot that has a wired/wireless internet connection (e.g., MiFi), or any other wired or wireless connection suitable for communicating signals with network 140.

FIG. 3 depicts a block diagram of POS data collector 105, in accordance with certain exemplary embodiments. Components of POS data collector 105 may include, but are not limited to, processor 360, storage resource 362, network module 364, input/output (I/O) module 366, clock module 368, GPS module 370, and error indicator 130 (error indicator 130 is also depicted in FIGS. 1 and 2). As depicted processor 360 may be communicatively coupled to each of the other components of POS data collector 105.

Processor 360 may comprise any system, device, or apparatus operable to interpret and/or execute program instructions and/or process data associated with software module 380, and may include, without limitation a microprocessor, microcontroller, digital signal processor (DSP), application specific integrated circuit (ASIC), or any other digital or analog circuitry configured to interpret and/or execute program instructions and/or process data. In some embodiments, processor 360 may interpret and/or execute program instructions and/or process data stored locally (e.g., in storage resource 362). In the same or alternative embodiments, processor 360 may interpret and/or execute program instructions and/or process data stored remotely (e.g., in a network storage resource (not depicted) of network 140 of FIGS. 1 and 2).

Local storage resource 362 may comprise computer-readable media (e.g., hard disk drive, floppy disk drive, CD-ROM, and/or other type of rotating storage media, flash memory, EEPROM, and/or other type of solid state storage media) and may be generally operable to store data.

Network module 364 may be any suitable system, apparatus, or device operable to serve as an interface between information POS data collector 105 and network 140 (FIGS. 1 and 2). Network module 364 may enable information POS data collector 105 to communicate over network 140 using any suitable transmission protocol and/or standard, including without limitation all transmission protocols and/or standards enumerated above with respect to the discussion of network 140 and connection 135.

I/O module 366 may be any system, device, or apparatus generally operable to receive and/or transmit data to/from/within information POS data collector 105. I/O module 366 may comprise, for example, any number of communication interfaces, including without limitation a USB interface and/or an RS-232 interface.

Clock module 368 may be any system, device, or apparatus generally operable to maintain an internal clock. According to certain exemplary embodiments, clock module 368 may synchronize with the UTC (coordinated universal time). Additionally, clock module 368 may be configured to maintain an accurate internal clock when power to POS data collector 105 is removed (e.g., via an independent battery power source).

GPS module 370 may be any system, device, or apparatus generally operable to determine and provide the location of POS data collector 105 based on global positioning satellite signals or other similar methods (e.g., via location information received by network module 364).

Error indicator 130 may be any system, device, or apparatus generally operable to provide an indication that may be detected visually or audibly by a person near POS data collector 105. For example, error indicator 130 may be a visible LED light, in accordance with certain exemplary embodiments. In the same or alternative embodiments, error indicator may be an audible speaker capable of producing an audible noise.

FIG. 4 is a block flow diagram depicting a method 400 for collecting POS data, in accordance with certain exemplary embodiments. The method 400 is described with reference to components illustrated in FIGS. 1-3.

In block 405, a software module 380 of a POS data collector 105 may wait to obtain a product identifier associated with a product that is being purchased. For example, POS scanner 110 is used to scan the barcode of a product that is being purchased. After scanning, the POS scanner 110 transmits the product identifier for processing by a POS application running on POS terminal 115. Because the POS data collector 105 is communicatively coupled between POS scanner 110 and POS terminal 115, POS data collector 105 may obtain the product identifier associated with the purchased product as the identifier is transmitted to the POS terminal 115.

In block 410, software module 380 may transmit an unmodified version of the product identifier to POS terminal 115. In accordance with certain exemplary embodiments, this transmission may be performed without noticeable delay so that the addition of POS data collector 105 to POS system 100 does not interfere with the normal business flow. In other words, the POS application running on POS terminal 115 will be able to proceed with the purchase transaction, and will not be noticeably delayed by the addition of the POS data collector 105 to POS system 100.

In block 415, the software module 380 may establish a connection with remote system 150 via network module 364 and network 140. According to an exemplary embodiment, software module 380 may establish this connection by resolving the host name and/or address via DNS or other protocols, and subsequently communicating with remote system 150 to establish the connection. If a connection is successfully established (block 420), software module 380 may proceed to block 425 and may transmit the product identifier to remote host 150. According to certain exemplary embodiments, this transmission may be via the HTTPS protocol, or any other protocol suitable for communicating data over network 140 to remote system 150. According to exemplary embodiments that utilize the HTTPS protocol, software module 380 may verify the validity of the SSL certificate, and may not transmit data if validity is not established.

According to an exemplary embodiment, the data transmission in block 425 may include only the product identifier. In other embodiments, software module 380 may transmit additional data to remote server 150. In both cases, and according to the HTTPS protocol used in an exemplary embodiment, the transmitted data may be sent as a body of a POST request over HTTPS. Thus, when only the product identifier is transmitted, the body of the POST request may contain the following fields:

scan:<product_identifier>

In an alternative embodiment, software module 380 may provide additional data including, but not limited to, one or more of the following: a merchant identifier, a store identifier (e.g., for merchants with more than one store), a scanned product count, a current time stamp, a device identifier (e.g., a manufacturer-issued serial number), a security key (e.g., for secure communication), a software version number, price, and a device GPS coordinate. In accordance with this alternative embodiment, the body of the POST request may contain one or more of the following fields:

  serial:<device_identifier> key:<security key> version:<software version> currenttime:<current_time> sequence:<scanned_product_count> store:<store_identifier> gps:<gps_coordinates> scan:<product_identifier>

In yet another exemplary embodiment, software module 380 may provide a time stamp indicating when the product identifier was scanned by the POS scanner. According to this embodiment, the body of the POST requests depicted above may be modified as follows:

scan:<product_identifier>:<timestamp>

In block 445, software module 380 may determine if the transmission was successful. For example, according to a transmission via HTTPS, software module 380 may receive a HTTP 200/OK response with an empty body when the transmission is successful. Alternatively, software module 380 may receive either a 4xx or 5xx HTTP error if the transmission is unsuccessful.

If the data transmission is not successful (block 445), software module 380 may proceed to block 450, where it may determine if a predetermined retry count has been exceeded. If the retry count has not been exceeded, software module 380 may increment the retry count and proceed back to block 425 where it may again attempt to transmit the product identifier (and any other data, as described above) to remote system 150. According to an exemplary embodiment, software module 380 may proceed to block 425 immediately. In other embodiments, software module 380 may wait for a predetermined amount of time (e.g., 1, 5, 10, etc. minutes) before retrying the transmission. In yet another exemplary embodiment, software module 380 may wait for 1 minute before retrying (the “timeout interval”), and if the next attempted transmission is unsuccessful, double the timeout interval. In this embodiment, software module 380 may continue to double the timeout interval for each consecutive failed transmission attempt until the timeout interval is 32 minutes, at which point software module 380 may keep trying to transmit the data every 32 minutes.

In the event the number of transmission attempts exceeds the predetermined retry count in block 450, software module may proceed to block 440, and may activate error indicator 130. In this manner, an employee of the retail store may be notified that the POS data collector has encountered an error.

Similarly, if a connection is not successfully established (block 420), software module 380 may proceed to block 435, where it may determine if a predetermined retry count has been exceeded. If the retry count has not been exceeded, software module 380 may increment the retry count and proceed back to block 415 where it may again attempt to establish a connection with remote system 150. Here, a timeout interval algorithm similar to that described above may be used. In the event the number of connection attempts exceeds the predetermined retry count in block 435, software module may proceed to block 440, and may activate error indicator 130. In this manner, an employee of the retail store may be notified that the POS data collector has encountered an error.

In the event the error indicator is activated, software module 380 may proceed back to block 405, where it may wait to obtain the next product identifier associated with an additional product that is being purchased. Thus, software module 380 may continue to operate despite the error condition. In this manner, the POS data collector 105 may at least continue to transmit scanned product identifiers to the POS terminal (block 410) so that the error condition does not interfere with business operations. According to an exemplary embodiment (not depicted), software module 380 may, in such a case, deactivate the error indicator if a subsequent attempt to establish a connection with remote system 150 or to transmit data to remote system 150 is successful.

Thus, according to the exemplary embodiment of FIG. 4, POS data collector 105 may transmit each product identifier essentially in real time as each product is scanned and without significant delay (i.e., no more delay than is necessary for the method steps of FIG. 4 to be performed).

According to an exemplary embodiment and as an alternative to transmitting POS data in real time, POS data collector 105 may accumulate POS data and transmit the accumulated data to remote system 150 periodically. For example, software module 380 may store accumulated product identifiers in storage resource 362 until such time as they are transmitted to remote system 150. In one embodiment, for example, software module 380 may accumulate product identifiers for a predetermined amount of time (e.g., 5, 15, 30, etc. minutes) before transmitting the data to remote server 150. In yet another embodiment, software module 380 may accumulate product identifiers and may transmit the data to remote server 150 after a predetermined number of identifiers (e.g., 5, 100, 1000, etc.) have been accumulated.

In still a further embodiment, software module 380 may accumulate POS data and use both a time period and a predetermined product identifier count to determine when to transmit the data to remote system 150. According to this exemplary embodiment, software module 380 may buffer product identifiers for a predetermined amount of time or until a predetermined number of product identifiers are accumulated—whichever comes first. In still another embodiment, software module 380 may accumulate POS data until a predetermined amount of data is accumulated (e.g., 1 kB, 1 MB, etc.). Accordingly, the data transmission may be optimized to minimize traffic while still sending updates with reasonable frequency.

Thus, software module 380 may transmit only the accumulated product identifiers, in accordance with an exemplary embodiment. In such a case, the body of an HTTPS request may be formatted as follows:

  scan:<product_identifier>:<timestamp> scan:<product_identifier>:<timestamp> . . .

In embodiments where the software module 380 provides data in addition to the product identifiers, the body of the POST request may contain one or more of the following fields:

  serial:<device_identifier> key:<security key> version:<software version> currenttime:<current_time> sequence:<scanned_product_count> store:<store_identifier> gps:<gps_coordinates> scan:<product_identifier>:<timestamp> scan:<product_identifier>:<timestamp> . . .

In the exemplary embodiments described above, the connection to remote system 150 via network module 364 and network 140 may be kept open or may be closed between transmissions.

POS data collector 105 may transmit an alive indicator to remote system 150, in accordance with an exemplary embodiment. For example, regardless of whether any products are scanned, software module 380 may send an alive indicator to remote system 150 on a periodic basis (e.g., every 4, 6, 8, etc. hours). Software module 380 may transmit an alive indicator using steps similar to those described in FIG. 4. For example, software module 380 may perform the same retry/error algorithm when attempting to establish a connection with remote system 150 and to transmit the alive indicator.

According to exemplary embodiments that utilize the HTTPS protocol for transmission, the HTTPS transmission for an alive indicator may be directed to a URL that is different from the URL used for transmitting product identifier(s). In addition, the body of an alive indicator POST request may contain one or more of the following fields:

  serial:<device_identifier> key:<security key> version:<software version> currenttime:<current_time> sequence:<scanned_product_count>

Accordingly, remote system 150 may use the alive indicator transmission to monitor POS data collector 105 for errors. In other words, remote system 150 may determine that POS data collector 105 is not operating if it does not receive an alive indicator according to the predetermined periodic schedule. Thus, a POS data collection system provider can arrange to troubleshoot POS data collector 105 in the event it stops operating correctly.

FIG. 5 depicts a system 500 for extracting data, in accordance with certain exemplary embodiments. As depicted in FIG. 5, system 500 may comprise local computer 502, remote storage resource 508, remote computer 510, and remote databases 516. Local computer 502 may be a commercial retailer's central server located at the retailer's headquarters, or it may be a regional server, or a store-specific server. Database 504 may reside on local computer 502 or may reside on a remote database server (not pictured), and may contain data related to retail products and/or the business that sells products. For example, local computer 502 may be owned by a commercial retailer and database 504 may contain data related to the retailer's product inventory, the retailer's stores (e.g., businesses with more than one location), point of sale transactions, product listings, price-quantity data (e.g., per store, per product pricing), circulars, coupons, etc. According to exemplary embodiments, database 504 may be a commercially available database program (e.g., MySQL, Oracle, MS SQL Server, etc.). In alternative embodiments, database 504 may be part of commercially available product inventory/sales software, a flat data file, a spreadsheet, etc. Similarly, remote databases 516 may be of any type, but may be located remote to local computer 502.

According to exemplary embodiments, content extractor 506 may reside on local computer 512. Content extractor may be software that is generally operable to extract data from database 504, to process the extracted data, and to transmit data to remote storage 508 and/or remote computer 510. As illustrated, content extractor 506 may include a configuration file 514. Configuration file 514 may be any format, including binary, clear text, database, etc. Configuration file 514 may contain connection and mapping settings related to database 504, remote storage 508 and/or remote computer 510. Content extractor 506 and configuration file 514 are explained in detail with reference to FIGS. 6-8, below.

Remote storage 508 may be any storage facility accessible to both local computer 502 and remote computer 510. According to exemplary embodiments, remote storage 508 may include disk-based storage resources, such as magnetic storage, opto-magnetic storage, or any other type of disk-based storage. As depicted in FIG. 5, remote storage may be separate from local computer 502 and remote computer 510, e.g., as a stand-alone network attached storage solution, as a cloud storage solution, etc. Alternatively, remote storage 508 may form an integral part of remote computer 510, e.g., as a storage resource (or array of storage resources) residing on remote computer 510.

Remote computer 510 may be any instrumentality or aggregate of instrumentalities operable to compute, classify, process, transmit, receive, retrieve, originate, switch, store, display, manifest, detect, record, reproduce, handle, or utilize any form of information, intelligence, or data for business, scientific, control, entertainment, or other purposes. For example, an information handling system may be a mainframe computer, a network server, a personal computer, a PDA, a consumer electronic device, a network storage device, or any other suitable device and may vary in size, shape, performance, functionality, and price. Remote computer 510 may include memory, one or more processing resources such as a central processing unit (CPU) or hardware or software control logic. Additional components or the remote computer 510 may include one or more storage devices, one or more communications ports for communicating with external devices as well as various input and output (I/O) devices, such as a keyboard, a mouse, and a video display. The remote computer 510 may also include one or more buses operable to transmit communication between the various hardware components.

As further depicted in FIG. 5, local computer 502 may be communicatively coupled to remote storage 508 (if provided) and remote computer 510 via network 512. Network 512 may be implemented as, or may be a part of, a storage area network (SAN), personal area network (PAN), local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a wireless local area network (WLAN), a virtual private network (VPN), an intranet, the internet or any other appropriate architecture or system that facilitates the communication of signals, data and/or messages (generally referred to as data). According to an exemplary embodiment, local computer 502 may connect to network 512 via a dedicated cellular modem connection. In an alternative embodiment, local computer 502 may connect to network 512 via a wired Ethernet connection, a Wi-Fi or Bluetooth connection to a hotspot that has a wired/wireless internet connection (e.g., MiFi), or any other wired or wireless connection suitable for communicating signals over network 512.

FIG. 6 depicts a system 600 for extracting data, in accordance with certain exemplary embodiments. As depicted in FIG. 6, system 600 may include configuration dialogue 601. Configuration dialogue 601 may be presented by content extractor 506 to a user of local computer 502, and may be generally operable to accept input from the user. For example, configuration dialogue 601 may include a Database Type menu 602. According to certain exemplary embodiments, Database Type menu 602 may be a drop-down menu with a preconfigured selection of database types that are compatible with content extractor 506. For example, the Database Type menu 602 may contain entries for commercially available database programs (e.g., MySQL, Oracle, MS SQL Server, etc.), commercially available product inventory/sales software (e.g., POSlog, etc.), flat data files, spreadsheets, etc. Accordingly, a user of local computer 502 may select the appropriate entry in Database Type menu 602 that corresponds to database 504.

According to certain exemplary embodiments, configuration dialogue 601 may also include Database Host input 604 (with optional port number), Database Name input 606, DB Username input 608, and DB Password input 610. Accordingly, a user of local computer 502 may specify the connection parameters specific to database 504 so that content extractor 506 may obtain access to the data contained therein. While inputs 602-610 are explicitly depicted in FIG. 6, configuration dialogue 601 should not be limited to this specific embodiment. For example, additional inputs may be provided related to accessing database 504. Alternatively, some of the depicted inputs may not be necessary to access database 504 depending on the specific configuration of local computer 502 and database 504.

In addition to the database configuration parameters just described, configuration dialogue 601 may accept remote computer and/or remote storage configuration parameters. For example, in some embodiments, configuration dialogue 601 may include Remote Username input 612, Remote Password input 614, Schedule Frequency menu 616, Schedule Time input 618, and Schedule Day menu 619. According to certain exemplary embodiments, Schedule Frequency menu 616 may be a drop-down menu with a preconfigured selection of frequency types that are compatible with content extractor 506.

According to the depicted embodiment, Schedule Frequency menu 616 includes the “weekly” frequency type, indicating that content extractor 506 should extract data from database 504 and transmit the data to remote storage 508 and/or remote computer 510 on a weekly basis, for example, at 7:00 PM every Saturday (as specified by Schedule Time input 618 and Schedule Day menu 619). In other exemplary embodiments, Schedule Frequency menu 616 may contain entries for other periodic extraction frequencies, such as “monthly,” “daily,” “hourly,” etc.

In still another embodiment, Schedule Frequency menu 616 may contain an entry for “instant” or “manual” extraction. According to these embodiments, content extractor 506 may extract data from database 504 and transmit the data to remote storage 508 and/or remote computer 510 as soon as the user clicks Save button 622.

According to yet another exemplary embodiment, Schedule Frequency menu 616 may contain an entry for “real time” extraction. According to this embodiment, content extractor 506 may extract data from database 504 and transmit the data to remote storage 508 and/or remote computer 510 in real time. For example, real time extraction may occur in response to the updating of a database table in database 504. This may be useful, for example, to reflect a change of product pricing, a store closing, a promotion, a regional event, product sales (e.g., line item data reflecting recent sale information), or other change related to product sales and/or the business or store that sells the products. In other exemplary embodiments, real time extraction may occur in response to other predetermined events that are external to database 504 (e.g., local computer establishing connection with remote storage 508 and/or remote computer 510, content extractor establishing connection to database 504, etc.). These and other events that trigger real time extraction may be provided for in configuration file 514.

Thus, by providing parameters 612-619, a user of local computer 502 may specify the connection parameters specific to remote storage 508 and/or remote computer 510 so that content extractor 506 may connect and transmit data thereto. While inputs 612-619 are explicitly depicted in FIG. 6, configuration dialogue 601 should not be limited to this specific embodiment. For example, additional inputs may be provided related to accessing remote storage 508 and/or remote computer 510. Alternatively, some of the depicted inputs may not be necessary to access remote storage 508 and/or remote computer 510 depending on the specific configuration of local computer 502, remote storage 508, and remote computer 510.

According to exemplary embodiments, configuration dialogue 601 may include Test Connections button 620, Save button 622, and Clear button 624, which may provide the function indicated by each respective label. For example, Test Connections button 620 may use the user-supplied input parameters to test for a valid connection to the database 504, remote storage 508, and/or remote computer 510. Save button 622 may save the user-supplied input parameters to configuration file 514. Clear button 624 may clear all user-supplied input so that the input fields are blank and/or non-selected.

FIG. 7 depicts a system 700 for extracting data, in accordance with certain exemplary embodiments. As depicted in FIG. 7, system 700 may include table mapping dialogue 702. Table mapping dialogue 702 may be presented by content extractor 506 to a user of local computer 502, and may be generally operable to accept input from the user, where the input aids in mapping table attributes (e.g., table fields) in database 504 to predefined attributes in content extractor 506. In certain exemplary embodiments, table mapping dialogue 702 may be specific to a certain type of information, or table. For example FIG. 7 depicts a table mapping dialogue 702 that is specific to store information. According to this embodiment, the user may provide a mapping of table attributes related to store information (e.g., for a retailer with one or multiple stores). In other exemplary embodiments, table mapping dialogue 702 may be specific to product information (e.g., data related to all products that a specific retailer sells). In still other exemplary embodiments, table mapping dialogue 702 may be specific to price-quantity information (e.g., per store, per product inventory and pricing information). Still other embodiments of table mapping dialogue 702 may be provided, such that other data related to product sales and businesses that sell products may be collected.

According to certain exemplary embodiments, table mapping dialogue 702 may contain Table menu 704 of a drop-down menu type. The entries available on Table menu 704 may be provided based on the tables available in database 504 using connection parameters stored in configuration file 514. When the user selects a table using Table menu 704, the attributes of the selected table may appear in Table Attributes field 706. In the depicted example, selected table “stores” has three attributes: name, address, and id. Table mapping dialogue 702 may also contain Store Attributes field 708. Store Attributes field 708 may contain predefined attributes of content extractor 506. In this depicted embodiment, this field is labeled “Store Attributes” because, as discussed above, the table mapping dialogue 702 is specific to Store Information. In other embodiments, this field of table mapping dialogue 702 may have a different label (e.g., “Product Attributes,” “Price-Quantity Attributes,” etc.).

Accordingly, a user of local computer 502 may provide a mapping between the table attributes (shown in Table Attributes field 706) and the predefined attributes of content extractor 506 (shown, e.g., in Store Attributes field 708). For example, a user may select “name” from Table Attributes field 706 and “Name” from Store Attributes field 708 and press Save Map button 712. In the same manner, a user may map “address” to “Address Line 1,” and “id” to “Store Code.” The result of this example mapping is depicted in table mapping dialogue 720 of FIG. 7. Specifically, the mapping may be presented to the user in the manner depicted in Mapped Values field 726. According to exemplary embodiments and as depicted in mapping dialogue 720, once a table attribute is mapped, it may be removed from Table Attributes field 706. Likewise, once a store attribute is mapped, it may be removed from Store Attributes field 706.

According to exemplary embodiments, table mapping dialogue 702 may include Generate button 714, Save button 716, and Clear button 718, which may provide the function indicated by each respective label. For example, Generate button 714 may use the user-supplied input parameters to generate a file representing the data that content extractor 506 would transmit to remote storage 508 and/or remote computer 510. This may be useful, for example, to ensure that the user-supplied mapping is accurate. Save button 716 may save the user-supplied input parameters to configuration file 514 or a separate mapping file (not depicted). Clear button 624 may clear all user-supplied input so that the input fields are blank and/or revert to their initial state.

According to the features of the exemplary embodiments described above, a user of local computer 502 may easily provide a mapping of table attributes in existing, legacy database systems to the predefined attributes desired by content extractor 506.

FIG. 8 is a block flow diagram depicting a method 800 for extracting data, in accordance with certain exemplary embodiments. The method 800 is described with reference to components illustrated in FIGS. 5-7. FIG. 8 also illustrates a means for extracting data according to certain exemplary embodiments.

In block 802, a content extractor 506 may wait for a trigger condition. For example, such a trigger condition may be provided in accordance with the user-supplied parameters 616-619 of configuration dialogue 601. As described above, a trigger condition may be based on a periodic setting, an instant setting, or a real time setting. Once the configured trigger event occurs, content extractor 506 may proceed to block 804.

In block 804, content extractor 506 may read configuration file 514 to obtain database connection parameters in accordance with the user-supplied parameters 602-610 of configuration dialogue 601. Content extractor 506 may also obtain table mapping parameters in accordance with the user-supplied mapping provided in table mapping dialogue 702. In block 806, content extractor 506 may attempt to connect to database 504 using the obtained database connection parameters. If the connection attempt is successful, content extractor 506 may proceed to block 808.

In block 808, content extractor 506 may extract data from one or more database tables residing in database 504. For example, content extractor 506 may use the attribute mappings obtained in block 804 to extract data from the specified table fields. Additionally, content extractor 506 may extract data from one or more database tables residing in remote databases 516. In this manner, content extractor 506 can receive data from multiple databases located in the same or different locations. For example, a retailer may operate multiple stores that each store sales data. The content extractor 506 may receive the data from each database 504, 516 to provide a data source for all (or any given portion) of the retailer's distributed sales data.

In block 810, content extractor 506 may process the extracted data. For example, content extractor 506 may verify that the format of the extracted data matches an expected format (e.g., uniformity of address data, syntax, etc.). In certain embodiments, content extractor 506 may reformat extracted data if it does not match an expected format and not reformat the extracted data if it does match an expected format.

In the same or additional embodiments, in block 810 content extractor may auto-generate data based on the extracted data. For example, in some embodiments, content extractor 506 may desire the latitude and longitude information for a given store location. This information may not be available in database 504. Thus, content extractor 506 may be configured to generate latitude and longitude information based on an address of a store location where the address information is both available in database 504 and has been properly mapped using mapping dialogue 702. As just described, block 810 may illustrate a means for processing extracted data according to exemplary embodiments.

In block 812, content extractor 506 may attempt to connect to remote storage 508 and/or remote computer 510 using the remote storage and/or remote computer connection parameters obtained, for example, in block 804. If a the connection attempt is successful, content extractor 506 may proceed to block 814, where content extractor 506 may transmit the data (i.e., extracted data with additions/modifications as performed in block 810) to remote storage 508 and/or remote computer 510. After the data is transmitted, content extractor 506 may return to block 802, where it waits for the next trigger condition.

The exemplary methods and systems described in the embodiments presented previously are illustrative, and, in alternative embodiments, certain components/steps can be performed in a different order, in parallel with one another, omitted entirely, and/or combined between different exemplary methods, and/or certain additional components/steps can be performed, without departing from the scope and spirit of the invention. Accordingly, such alternative embodiments are included in the invention described herein.

The invention can be used with computer hardware and software that performs the methods and processing functions described above. As will be appreciated by those skilled in the art, the systems, methods, and procedures described herein can be embodied in a programmable computer, computer executable software, or digital circuitry. The software can be stored on computer readable media. For example, computer readable media can include a floppy disk, RAM, ROM, hard disk, removable media, flash memory, memory stick, optical media, magneto-optical media, CD-ROM, etc. Digital circuitry can include integrated circuits, gate arrays, building block logic, field programmable gate arrays (FPGA), etc. The systems and methods described herein can be implemented by one or more software modules operating in at least one computer system that comprises instructions stored in a machine-readable medium and a processor that executes the instructions.

Although specific embodiments of the invention have been described above in detail, the description is merely for purposes of illustration. Various modifications of, and equivalent blocks corresponding to, the disclosed aspects of the exemplary embodiments, in addition to those described above, can be made by those skilled in the art without departing from the spirit and scope of the invention defined in the following claims, the scope of which is to be accorded the broadest interpretation so as to encompass such modifications and equivalent structures. 

1. A computer-implemented method for extracting data, comprising: receiving a database connection parameter and a remote system connection parameter; establishing a connection with a database using the database connection parameter, the database comprising at least one table having at least one table attribute; receiving a mapping of one of the at least one table attributes to at least one predefined attribute; extracting data from the database based on the mapping; establishing a connection with a remote system using the remote system connection parameter; and transmitting the extracted data to the remote system, wherein the method is implemented by a software module in at least one computer system that comprises instructions stored in a machine-readable medium and a processor that executes the instructions.
 2. The method of claim 1, wherein the extracted data comprises at least one of product sales data and commercial retailer data.
 3. The method of claim 1, wherein the extracted data comprises product inventory data.
 4. The method of claim 1, wherein the remote system comprises a remote storage system and a remote computer.
 5. The method of claim 1, wherein the steps of extracting data from the database and transmitting the extracted data to the remote system occur in response to a predetermined event.
 6. The method of claim 5, wherein the predetermined event is a time of day.
 7. The method of claim 5, wherein the predetermined event is an updating of the at least one table.
 8. The method of claim 5, wherein the predetermined event is external to the database.
 9. The method of claim 5, wherein the extracted data comprises at least one of product sales data and commercial retailer data.
 10. The method of claim 1, wherein the database is a remote database.
 11. The method of claim 1, wherein the database comprises multiple databases.
 12. The method of claim 1, further comprising means for processing the extracted data.
 13. The method of claim 1, further comprising: auto-generating, based on the extracted data, data corresponding to at least one predefined attribute for which a mapping has not been obtained; and transmitting the auto-generated data to the remote system along with the extracted data.
 14. A data extraction system, comprising: a storage resource; a network module; a database comprising a table having one or more table attributes; a processor communicatively coupled to the storage resource and the network module, wherein the processor executes application code instructions that are stored in the storage resource and that cause the data extraction system to: receive a database connection parameter, a remote system connection parameter, and a mapping of at least one table attribute to a predefined attribute; establish a connection with the database using the database connection parameter; extract data from the database based on the mapping; process the extracted data; establish, via the network module, a connection with a remote system using the remote system connection parameter; and transmit, via the network module, the processed data to the remote system.
 15. The data extraction system of claim 14, wherein the application code instructions further cause the data extraction system to: receive a schedule for extracting data from the database; and extract, process, and transmit data from the database to the remote system according to the received schedule.
 16. The data extraction system of claim 15, wherein the schedule is one of a predetermined time of day, a predetermined day, instantly in response to a database update event, and in response to an event that is external to the database.
 17. A data extraction system, comprising: a storage resource; a network module; a display; a database comprising a table having one or more table attributes; a processor communicatively coupled to the storage resource and the network module, wherein the processor executes application code instructions that are stored in the storage resource and that cause the data extraction system to: provide, on the display, at least one graphical user interface comprising inputs for receiving a database connection parameter, a remote system connection parameter, a one-to-one mapping of at least one table attribute to a predefined attribute, and a schedule for extracting data from the database; receive the database connection parameter, the remote system connection parameter, the mapping, and the schedule; establish, in accordance with the schedule, a connection with the database using the database connection parameter; extract, in accordance with the schedule, data from the database using the mapping; process, in accordance with the schedule, the extracted data; establish, in accordance with the schedule and via the network module, a connection with a remote system using the remote system connection parameter; and transmit, in accordance with the schedule and via the network module, the processed data to the remote system.
 18. A data extraction system, comprising: one or more processors for executing programs; a network interface for receiving and transmitting data; a storage resource containing one or more data objects, each data object having one or more attributes; and a data extraction engine executable by the one or more processors, the engine comprising: instructions for obtaining a mapping of the one or more attributes to one or more predefined attributes; instructions for extracting data from the storage resource based on the mapping; and instructions for transmitting the data to a remote system via the network interface.
 19. A computer program product for use in conjunction with a computer system and a database comprising a table having one or more table attributes, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising: instructions for receiving a database connection parameter, a remote system connection parameter, and a mapping of at least one table attribute to a predefined attribute; instructions for establishing a connection with the database using the database connection parameter; instructions for extracting data from the database based on the mapping; instructions for establishing a connection with a remote system using the remote system connection parameter; and instructions for transmitting the processed data to the remote system.
 20. A computer program product for use in conjunction with a computer system and a database comprising data objects having one or more attributes, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising: instructions for receiving a mapping of at least one data object attribute to a predefined attribute; instructions for extracting data from the database based on the mapping; and instructions for transmitting the extracted data to a remote system.
 21. A data extraction system, comprising: a storage resource; a network module; a database comprising a table having one or more table attributes; a processor communicatively coupled to the storage resource and the network module, wherein the processor executes application code instructions that are stored in the storage resource; and a means for extracting data from the database. 